scholarly journals Improved methods of maximum a posteriori image restoration

1976 ◽  
Author(s):  
H Trussell
Keyword(s):  
Image Restoration ◽  
Maximum A Posteriori ◽  
A Posteriori ◽  
Improved Methods

scholarly journals Image Restoration using Mirroring Method Which Based on the Gradient Direction

2020 ◽  
Vol 188 ◽  
pp. 00011
Author(s):  
I Komang Somawirata ◽  
Aryuanto Soetedjo ◽  
Sotyohadi Sotyohadi ◽  
Fitri Utaminingrum ◽  
Maizirwan Mel
Keyword(s):  
Image Restoration ◽  
Previous Method ◽  
Maximum A Posteriori ◽  
A Posteriori ◽  
Gradient Direction ◽  
Degraded Image ◽  
Image Area

Restoring a damaged image is a challenging topic in the field of image restoration. The famous previous method for restoring a degraded image are filters (inverse and wiener) and maximum a posteriori (MAP) formulation. However, that method has limited performance for restoring damaged images. In this paper, the multi mirroring method have been implemented for reconstructing damaged image which based on gradient direction. Firstly, the method will detect damaged image areas and then the multi mirroring method is implemented for filling a damaged image area. The simulation result shows that the proposed method has good result and capable to restore the damaged image.

Fuzzy logic and maximum a posteriori-based image restoration for confocal microscopy

2006 ◽  
Vol 31 (24) ◽  
pp. 3582 ◽  
Author(s):  
Giuseppe Vicidomini ◽  
Partha Pratim Mondal ◽  
Alberto Diaspro
Keyword(s):  
Fuzzy Logic ◽  
Confocal Microscopy ◽  
Image Restoration ◽  
Maximum A Posteriori ◽  
A Posteriori

scholarly journals Threshold Computation for Spatially Coupled Turbo-Like Codes on the AWGN Channel

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 240
Author(s):  
Muhammad Umar Farooq ◽  
Alexandre Graell i Amat ◽  
Michael Lentmaier
Keyword(s):  
Gaussian Noise ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Maximum A Posteriori ◽  
Prediction Methods ◽  
Threshold Analysis ◽  
A Posteriori ◽  
Awgn Channel ◽  
Efficient Prediction ◽  
Binary Erasure Channel

In this paper, we perform a belief propagation (BP) decoding threshold analysis of spatially coupled (SC) turbo-like codes (TCs) (SC-TCs) on the additive white Gaussian noise (AWGN) channel. We review Monte-Carlo density evolution (MC-DE) and efficient prediction methods, which determine the BP thresholds of SC-TCs over the AWGN channel. We demonstrate that instead of performing time-consuming MC-DE computations, the BP threshold of SC-TCs over the AWGN channel can be predicted very efficiently from their binary erasure channel (BEC) thresholds. From threshold results, we conjecture that the similarity of MC-DE and predicted thresholds is related to the threshold saturation capability as well as capacity-approaching maximum a posteriori (MAP) performance of an SC-TC ensemble.

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